Spatial Organization of the Gene Regulatory Program: An Information Theoretical Approach to Breast Cancer Transcriptomics

Anda-Jáuregui, Guillermo de; Espinal-Enríquez, Jesús; Hernández‐Lemus, Enrique

doi:10.3390/e21020195

Cited by 13 publications

(14 citation statements)

References 17 publications

(28 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(1) pre-normalization quality control, (2) batch and bias corrections (normalization) and (3) post-normalization quality control. Data pre-processing was conducted as previously (Drago-García et al, 2017 ; Espinal-Enriquez et al, 2017 ; de Anda-Jáuregui et al, 2019b , c ; García-Cortés et al, 2020 ; Serrano-Carbajal et al, 2020 ). Briefly, we assessed (a) biotype abundances, to assure that samples contained protein coding genes.…”

Section: Methodsmentioning

confidence: 99%

“…Since a relevant question underlies on whether in these networks, the effect of loss of trans- co-expression was also lost as in breast cancer (Espinal-Enriquez et al, 2017 ; de Anda-Jáuregui et al, 2019a , b , c ; Dorantes-Gilardi et al, 2020 ; García-Cortés et al, 2020 ), we separated co-expression interactions into cis- (intra-chromosome), and trans- (inter-chromosome). We observed the cis-/trans- ratio for each phenotype.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Gene Expression and Co-expression Networks Are Strongly Altered Through Stages in Clear Cell Renal Carcinoma

2020

Self Cite

View full text Add to dashboard Cite

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Gene Expression and Co-expression Networks Are Strongly Altered Through Stages in Clear Cell Renal Carcinoma

2020

Self Cite

View full text Add to dashboard Cite

“…Previously, by comparing the gene co-expression network derived from RNA-Seq data from the unclassified breast cancer samples in TCGA and the co-expression network from the healthy samples, we reported a significant reduction in the number of interactions linking inter-chromosomal genes (trans-) and an increase on the strength of co-expression between intra-chromosomal (cis-) genes (29,30). On the other hand, in the healthy breast tissue, gene co-expression was apparently independent of the chromosome location of genes.…”

Section: Introductionmentioning

confidence: 99%

Gene Co-expression Is Distance-Dependent in Breast Cancer

et al. 2020

Self Cite

View full text Add to dashboard Cite

Breast carcinomas are characterized by anomalous gene regulatory programs. As is well-known, gene expression programs are able to shape phenotypes. Hence, the understanding of gene co-expression may shed light on the underlying mechanisms behind the transcriptional regulatory programs affecting tumor development and evolution. For instance, in breast cancer, there is a clear loss of inter-chromosomal (trans-) co-expression, compared with healthy tissue. At the same time cis-(intra-chromosomal) interactions are favored in breast tumors. In order to have a deeper understanding of regulatory phenomena in cancer, here, we constructed Gene Co-expression Networks by using TCGA-derived RNA-seq whole-genome samples corresponding to the four breast cancer molecular subtypes, as well as healthy tissue. We quantify the cis-/trans-co-expression imbalance in all phenotypes. Additionally, we measured the association between co-expression and physical distance between genes, and characterized the ratio of intra/inter-cytoband interactions per phenotype. We confirmed loss of trans-co-expression in all molecular subtypes. We also observed that gene cis-co-expression decays abruptly with distance in all tumors in contrast with healthy tissue. We observed co-expressed gene hotspots, that tend to be connected at cytoband regions, and coincide accurately with already known copy number altered regions, such as Chr17q12, or Chr8q24.3 for all subtypes. Our methodology recovered different alterations already reported for specific breast cancer subtypes, showing how co-expression network approaches might help to capture distinct events that modify the cell regulatory program.

show abstract

“…Previously, by comparing the gene co-expression network derived from RNA-Seq data from the unclassified breast cancer samples in TCGA and the co-expression network from the healthy samples, we reported a significant reduction in the number of interactions linking inter-chromosomal genes (trans-) and an increase on the strenght of co-expresssion between intra-chromosomal (cis-) genes [29,30]. On the other hand, in the healthy breast tissue, gene co-expression was apparently independent of the chromosome location of genes.…”

Section: Introductionmentioning

confidence: 99%

Gene co-expression is distance-dependent in breast cancer

García-Cortés

Anda-Jáuregui²,

Fresno³

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

Breast carcinomas are characterized by anomalous gene regulatory programs. As is well known, gene expression programs are able to shape phenotypes. Hence, the understanding of gene co-expression may shed light on the underlying mechanisms behind the transcriptional regulatory programs affecting tumor development and evolution. For instance, in breast cancer, there is a clear loss of inter-chromosomal (trans-) co-expression, compared with healthy tissue. At the same time cis-(intrachromosomal) interactions are favored in breast tumors. In order to have a deeper understanding of regulatory phenomena in cancer, here, we constructed Gene Coexpression Networks by using 848 RNA-seq whole-genome samples corresponding to the four breast cancer molecular subtypes, as well as healthy tissue. We quantify the cis-/trans-co-expression imbalance in all phenotypes. Additionally, we measured the association between co-expression and physical distance between genes, and characterized the proportion of intra/inter-cytoband interactions per phenotype. We confirmed loss of trans-co-expression in all molecular subtypes. We also observed that gene cis-co-expression decays abruptly with distance in all tumors in contrast with healthy tissue. We observed co-expressed gene hotspots, that tend to be connected at cytoband regions, and coincide accurately with already known copy number altered regions, such as Chr17q12, or Chr8q24.3 for all subtypes. Our methodology recovered different alterations already reported for specific breast cancer subtypes, showing how co-expression network approaches might help to capture distinct events that modify the cell regulatory program.

show abstract

Spatial Organization of the Gene Regulatory Program: An Information Theoretical Approach to Breast Cancer Transcriptomics

Cited by 13 publications

References 17 publications

Gene Expression and Co-expression Networks Are Strongly Altered Through Stages in Clear Cell Renal Carcinoma

Gene Expression and Co-expression Networks Are Strongly Altered Through Stages in Clear Cell Renal Carcinoma

Gene Co-expression Is Distance-Dependent in Breast Cancer

Gene co-expression is distance-dependent in breast cancer

Contact Info

Product

Resources

About